TY - JOUR
KW - Computer Simulation
KW - Decision Support Techniques
KW - Humans
KW - Massachusetts
KW - Naloxone/supply & distribution
KW - Narcotic Antagonists/supply & distribution
KW - Opiate Overdose/mortality
KW - Opiate Substitution Treatment/statistics & numerical data
KW - Retention in Care/statistics & numerical data
KW - Rural Population
KW - Urban Population
AU - B. P. Linas
AU - A. Savinkina
AU - R. W. M. A. Madushani
AU - J. Wang
AU - Eftekhari Yazdi
AU - A. Chatterjee
AU - A . Y. Walley
AU - J. R. Morgan
AU - R. L. Epstein
AU - S. A. Assoumou
AU - S. M. Murphy
AU - B. R. Schackman
AU - S. A. Chrysanthopoulou
AU - L. F. White
AU - J. A. Barocas
A1 - 
AB - IMPORTANCE: The United States is experiencing a crisis of opioid overdose. In response, the US Department of Health and Human Services has defined a goal to reduce overdose mortality by 40% by 2022. OBJECTIVE: To identify specific combinations of 3 interventions (initiating more people to medications for opioid use disorder [MOUD], increasing 6-month retention with MOUD, and increasing naloxone distribution) associated with at least a 40% reduction in opioid overdose in simulated populations. DESIGN, SETTING, AND PARTICIPANTS: This decision analytical model used a dynamic population-level state-transition model to project outcomes over a 2-year horizon. Each intervention scenario was compared with the counterfactual of no intervention in simulated urban and rural communities in Massachusetts. Simulation modeling was used to determine the associations of community-level interventions with opioid overdose rates. The 3 examined interventions were initiation of more people to MOUD, increasing individuals' retention with MOUD, and increasing distribution of naloxone. Data were analyzed from July to November 2020. MAIN OUTCOMES AND MEASURES: Reduction in overdose mortality, medication treatment capacity needs, and naloxone needs. RESULTS: No single intervention was associated with a 40% reduction in overdose mortality in the simulated communities. Reaching this goal required use of MOUD and naloxone. Achieving a 40% reduction required that 10% to 15% of the estimated OUD population not already receiving MOUD initiate MOUD every month, with 45% to 60%% retention for at least 6 months, and increased naloxone distribution. In all feasible settings and scenarios, attaining a 40% reduction in overdose mortality required that in every month, at least 10% of the population with OUD who were not currently receiving treatment initiate an MOUD. CONCLUSIONS AND RELEVANCE: In this modeling study, only communities with increased capacity for treating with MOUD and increased MOUD retention experienced a 40% decrease in overdose mortality. These findings could provide a framework for developing community-level interventions to reduce opioid overdose death.
AD - Section of Infectious Diseases, Boston Medical Center, Boston, Massachusetts.; Boston University School of Medicine, Boston, Massachusetts.; Section of Infectious Diseases, Boston Medical Center, Boston, Massachusetts.; Section of Infectious Diseases, Boston Medical Center, Boston, Massachusetts.; Section of Infectious Diseases, Boston Medical Center, Boston, Massachusetts.; Section of Infectious Diseases, Boston Medical Center, Boston, Massachusetts.; Clinical Addiction Research and Education Unit, Section of General Internal Medicine, Department of Medicine, Boston University School of Medicine, Boston, Massachusetts.; Grayken Center for Addiction at Boston Medical Center, Boston, Massachusetts.; Clinical Addiction Research and Education Unit, Section of General Internal Medicine, Department of Medicine, Boston University School of Medicine, Boston, Massachusetts.; Grayken Center for Addiction at Boston Medical Center, Boston, Massachusetts.; Boston University School of Public Health, Boston, Massachusetts.; Section of Infectious Diseases, Boston Medical Center, Boston, Massachusetts.; Boston University School of Medicine, Boston, Massachusetts.; Section of Infectious Diseases, Boston Medical Center, Boston, Massachusetts.; Boston University School of Medicine, Boston, Massachusetts.; Boston University School of Public Health, Boston, Massachusetts.; Department of Healthcare Quality and Research, Weill Cornell Medical College, New York, New York.; Boston University School of Public Health, Boston, Massachusetts.; Department of Healthcare Quality and Research, Weill Cornell Medical College, New York, New York.; School of Public Health, Brown University, Providence, Rhode Island.; Boston University School of Public Health, Boston, Massachusetts.; Section of Infectious Diseases, Boston Medical Center, Boston, Massachusetts.; Boston University School of Medicine, Boston, Massachusetts.
BT - JAMA network open
C5 - Healthcare Policy; Opioids & Substance Use
CP - 2
DO - 10.1001/jamanetworkopen.2020.37259
IS - 2
JF - JAMA network open
LA - eng
M1 - Journal Article
N2 - IMPORTANCE: The United States is experiencing a crisis of opioid overdose. In response, the US Department of Health and Human Services has defined a goal to reduce overdose mortality by 40% by 2022. OBJECTIVE: To identify specific combinations of 3 interventions (initiating more people to medications for opioid use disorder [MOUD], increasing 6-month retention with MOUD, and increasing naloxone distribution) associated with at least a 40% reduction in opioid overdose in simulated populations. DESIGN, SETTING, AND PARTICIPANTS: This decision analytical model used a dynamic population-level state-transition model to project outcomes over a 2-year horizon. Each intervention scenario was compared with the counterfactual of no intervention in simulated urban and rural communities in Massachusetts. Simulation modeling was used to determine the associations of community-level interventions with opioid overdose rates. The 3 examined interventions were initiation of more people to MOUD, increasing individuals' retention with MOUD, and increasing distribution of naloxone. Data were analyzed from July to November 2020. MAIN OUTCOMES AND MEASURES: Reduction in overdose mortality, medication treatment capacity needs, and naloxone needs. RESULTS: No single intervention was associated with a 40% reduction in overdose mortality in the simulated communities. Reaching this goal required use of MOUD and naloxone. Achieving a 40% reduction required that 10% to 15% of the estimated OUD population not already receiving MOUD initiate MOUD every month, with 45% to 60%% retention for at least 6 months, and increased naloxone distribution. In all feasible settings and scenarios, attaining a 40% reduction in overdose mortality required that in every month, at least 10% of the population with OUD who were not currently receiving treatment initiate an MOUD. CONCLUSIONS AND RELEVANCE: In this modeling study, only communities with increased capacity for treating with MOUD and increased MOUD retention experienced a 40% decrease in overdose mortality. These findings could provide a framework for developing community-level interventions to reduce opioid overdose death.
PY - 2021
SN - 2574-3805; 2574-3805
T1 - Projected Estimates of Opioid Mortality After Community-Level Interventions
T2 - JAMA network open
TI - Projected Estimates of Opioid Mortality After Community-Level Interventions
U1 - Healthcare Policy; Opioids & Substance Use
U2 - 33587136
U3 - 10.1001/jamanetworkopen.2020.37259
VL - 4
VO - 2574-3805; 2574-3805
Y1 - 2021
Y2 - Feb 1
ER -